Real time emotion recognition
Recognizing emotion from facial expression is a fundamental aspect of interpersonal communication. Children with diseases like autism spectrum disorder, Asperger’s Syndrome, often face difficulties trying to understand other people’s emotions. Consequently, such children need to be taught explicitly...
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2017
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sg-ntu-dr.10356-704432023-03-03T20:23:24Z Real time emotion recognition Cheang, Khai Mun Smitha Kavallur Pisharath Gopi School of Computer Science and Engineering DRNTU::Engineering::Computer science and engineering Recognizing emotion from facial expression is a fundamental aspect of interpersonal communication. Children with diseases like autism spectrum disorder, Asperger’s Syndrome, often face difficulties trying to understand other people’s emotions. Consequently, such children need to be taught explicitly how to read other people’s mood from nonverbal communication channels such as the facial expressions. For this project, I will try to estimate real time emotion recognition of 6 basic emotion proposed by Ekman (1972) [1]: Anger, Disgust, Happy, Sad and surprise plus one additional neutral emotion from input videos. This paper will focus on comparing different method of feature extractor and machine learning algorithms and implement the most suitable method in real time emotion recognition. The facial expression recognition software is written in python, with machine learning library like OpenCV, Scikit-learn. The proposed method has achieved 87.78% of accuracy with 7 emotions. Bachelor of Engineering (Computer Science) 2017-04-24T07:48:12Z 2017-04-24T07:48:12Z 2017 Final Year Project (FYP) http://hdl.handle.net/10356/70443 en Nanyang Technological University 39 p. application/pdf |
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DRNTU::Engineering::Computer science and engineering Cheang, Khai Mun Real time emotion recognition |
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Recognizing emotion from facial expression is a fundamental aspect of interpersonal communication. Children with diseases like autism spectrum disorder, Asperger’s Syndrome, often face difficulties trying to understand other people’s emotions. Consequently, such children need to be taught explicitly how to read other people’s mood from nonverbal communication channels such as the facial expressions. For this project, I will try to estimate real time emotion recognition of 6 basic emotion proposed by Ekman (1972) [1]: Anger, Disgust, Happy, Sad and surprise plus one additional neutral emotion from input videos. This paper will focus on comparing different method of feature extractor and machine learning algorithms and implement the most suitable method in real time emotion recognition. The facial expression recognition software is written in python, with machine learning library like OpenCV, Scikit-learn. The proposed method has achieved 87.78% of accuracy with 7 emotions. |
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Smitha Kavallur Pisharath Gopi |
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Smitha Kavallur Pisharath Gopi Cheang, Khai Mun |
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Final Year Project |
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Cheang, Khai Mun |
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Cheang, Khai Mun |
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Real time emotion recognition |
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Real time emotion recognition |
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Real time emotion recognition |
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Real time emotion recognition |
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Real time emotion recognition |
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real time emotion recognition |
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2017 |
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http://hdl.handle.net/10356/70443 |
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